A Traffic Analysis on Serverless Computing Based on the Example of a File Upload Stream on AWS Lambda

Muller, Lisa; Chrysoulas, Christos; Pitropakis, Nikolaos; Barclay, Peter J.

Abstract

The shift towards microservisation which can be observed in recent developments of the cloud landscape for applications has led towards the emergence of the Function as a Service (FaaS) concept, also called Serverless. This term describes the event-driven, reactive programming paradigm of functional components in container instances, which are scaled, deployed, executed and billed by the cloud provider on demand. However, increasing reports of issues of Serverless services have shown significant obscurity regarding its reliability. In particular, developers and especially system administrators struggle with latency compliance. In this paper, following a systematic literature review, the performance indicators influencing traffic and the effective delivery of the provider’s underlying infrastructure are determined by carrying out empirical measurements based on the example of a File Upload Stream on Amazon’s Web Service Cloud. This popular example was used as an experimental baseline in this study, based on different incoming request rates. Different parameters were used to monitor and evaluate changes through the function’s logs. It has been found that the so-called Cold-Start, meaning the time to provide a new instance, can increase the Round-Trip-Time by 15%, on average. Cold-Start happens after an instance has not been called for around 15 min, or after around 2 h have passed, which marks the end of the instance’s lifetime. The research shows how the numbers have changed in comparison to earlier related work, as Serverless is a fast-growing field of development. Furthermore, emphasis is given towards future research to improve the technology, algorithms, and support for developers.

Citation

Muller, L., Chrysoulas, C., Pitropakis, N., & Barclay, P. J. (2020). A Traffic Analysis on Serverless Computing Based on the Example of a File Upload Stream on AWS Lambda. Big Data and Cognitive Computing, 4(4), Article 38. https://doi.org/10.3390/bdcc4040038

• Journal Article Type: Article
• Acceptance Date: Dec 7, 2020
• Online Publication Date: Dec 10, 2020
• Publication Date: 2020-12
• Deposit Date: Dec 12, 2020
• Publicly Available Date: Dec 14, 2020
• Journal: Big Data and Cognitive Computing
• Print ISSN: 2504-2289
• Publisher: MDPI
• Peer Reviewed: Peer Reviewed
• Volume: 4
• Issue: 4
• Article Number: 38
• DOI: https://doi.org/10.3390/bdcc4040038
• Keywords: serverless computing; cloud computing; AWS Lambda; traffic analysis; FaaS; performance
• Public URL: http://researchrepository.napier.ac.uk/Output/2710837